Welcome Tobias Sichert - New Assistant Professor
The Swedish House of Finance and the Department of Finance at the Stockholm School of Economics recently welcomed new Assistant Professor Tobias Sichert - a PhD graduate from Goethe University and principal researcher in asset pricing. The first thing that drew Mr. Sichert to SHoF was the clear dedication of the department, a dedication to research. His impression became all the more clear when visiting the department and he enthusiastically looks forward to integrating with colleagues and starting joint projects.
Mr. Sichert grew up in the outskirts of the town Regensburg, located in the Bavarian state of Southern Germany. He later moved to Munich to study business administration at Ludwig Maximilian University of Munich and subsequently completed his masters there. While writing his master thesis, Mr. Sichert discovered a research passion for exploration without limits. It became a stepping stone in pursuing an internationally oriented PhD at Goethe University. During his PhD, he worked in the financial industry alongside his studies for a mutual fund due to his interest to go into the financial industry. Incrementally, Mr. Sichert slowly became increasingly fascinated by the possibility to continue his journey into academia. A decision he says was “less driven by any research topic in itself and more about the ‘fun in thinking and exploration’.
Today, Mr. Sichert primarily investigates what insights can be drawn from asset prices about investors’ preferences, perception of risks, what risk premia are demanded by the market and how they are linked to economic fundamentals. Understanding asset prices is of crucial importance in modern finance and macroeconomics. For instance, a firm’s investment decisions are influenced by the risk premia the market demands for its financing. People’s private investment and saving decisions strongly depend on expected returns and risks.
Going forward, Mr. Sichert plans to broaden the scope of his research to further prominent questions in asset pricing. A particular area which fascinates him is how machine learning techniques can be applied to finance. Currently, he is planning to study this in the context of a specific type of data, namely option data. Options are specific financial products that are heavily traded by professional investors. In a recently started project, he finds that a machine-learning approach offers a promising solution to several problems that emerge when studying the cross-section of option returns. They employ a wide range of state-of-the-art machine learning methods, including boosted regression trees, random forests and neural networks. Applying such techniques is a relatively new but rapidly growing approach. Despite being in its early stages, he underscores that it could potentially be a very promising method.
During his first year at the department, Mr. Sichert will teach an introduction class in finance to bachelor students in retail management and next year he plans to teach an empirical asset pricing course for a PhD class, something which is very close to his own research. In addition, Mr. Sichert and some colleagues will teach various short classes to PhD students about their own research to provide students with an overview of various fields and allow them to explore different avenues and research agendas. On behalf of SHoF and Department of Finance we are delighted to welcome Mr. Sichert and look forward to reading more about his future projects.